Image recoloring method for people with protanopia and deuteranopia

As a result of the conducted research, a method was developed to help people with the most common forms of dichromacy – deuteranopia and protanopia. For people with protanopia, the transformation of colors with a predominant red component is carried out, for deuteranopes – with a predominant green component. The features of the described method are finding colors indistinguishable for dichromats using a customizable colorimetric deviation and changing the coordinates b and L of indistinguishable colors in such a way that as a result of the transformations, the indistinguishable colors of one image differ from each other as much as possible, but at the same time retain their naturalness in the best possible way. Among the advantages of this method, it is worth noting the ability for each user to customize such personalized recoloring parameters as the colorimetric deviation of indistinguishable colors, the transformation coefficient of coordinate b, and the transformation coefficient of brightness L in accordance with their individual perception of visual information. Recoloring according to the developed method is acceptable for both more realistic images and for charts, signs, HTML-documents, and application interfaces. The correctness of the method was verified by examining a recolored image simulated by the Brettel et al. method for deuteranopic and protanopic vision with a normal trichromat, as a result of which areas of the image previously inaccessible to the dichromat's vision became distinguishable. The quality of recoloring was also assessed by the loss of color naturalness and global chromatic diversity. Thus, the loss of color naturalness for the test images had satisfactory values and varied within the range from 4.39 to 20.15 depending on the color component of the images. The global chromatic diversity of all test images was increased as a result of recoloring. The execution time of the method for both dichromacy cases indicates a satisfactory image processing speed and is 3 s for images of 170 000 pixels.

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